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S4 conference

Confirmed Speakers

SAFE TESTING

A large fraction (some claim > 1/2) of published research in top journals in applied sciences such as medicine and psychology is irreproduceable. In light of this ‘replicability crisis’, standard p-value based hypothesis testing has come under intense scrutiny. One of its many problems is the following: if our test result is promising but nonconclusive…

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A Critical Perspective on the Analysis of Event-Related Potentials based on Averages – Juan Carlos Oliver Rodríguez

Repeated measures Anova or Manova are frequently used for analyzing event-related brain potentials. They are typically performed on averaged repeated stimulus trials as a way of increasing the reliability of the electroencephalogram signal. Averaging, however, leads to information loss concerning the covariance matrix of random individual differences of participant treatment and time effects, which could…

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But are they similar enough? Accounting for between-study heterogeneity when specifying informative prior distributions in small-sample situations – Christoph Koenig

Bayesian methods have repeatedly shown to be advantageous for small-sample situations. To benefit from these advantages, researchers are required to quantify existing background information in informative prior distributions, which are currently used only scarcely. A prominent reason for this may be the distinct heterogeneity of studies in psychological and educational research. Studies are being conducted…

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Boosting Small Probability Samples with Nonprobability Sample Information – Joseph Sakshaug

Scientific surveys based on random probability samples are ubiquitously used in the social sciences to study and describe large populations. They provide a critical source of quantifiable information used by governments and policy-makers to make informed decisions. However, probability-based surveys are increasingly expensive to carry out and declining response rates observed over recent decades have…

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Finding the needle in the haystack with Active Learning – Gerbrich Ferdinands

Scholars are confronted with ever-larger amounts of textual data. All this data present new and unique opportunities to scholars, while simultaneously confronting them with unprecedented challenges. How to select relevant text effectively and efficiently from an almost unlimited amount of data? Conducting a systematic review on this data is often a very time consuming and…

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Investigating the impact of residualized likelihoods in Bayesian multilevel models with normal residuals – Jonathan Templin

Multilevel models (i.e., mixed-effects models) are used to predict outcomes with one or more sources of dependency, such as in clustered observations or repeated measures. In frequentist settings, the dominant estimation method for multilevel models with normally distributed residuals at each level (i.e., general linear mixed-effects models) is residual maximum likelihood (REML), which provides unbiased…

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